A heterogeneous short-range communication platform for Internet of Vehicles

International Journal of Electrical and Computer Engineering (IJECE)
Vol. 11, No. 3, June 2021, pp. 2165~2177
ISSN: 2088-8708, DOI: 10.11591/ijece.v11i3.pp2165-2177  2165
Journal homepage: http://ijece.iaescore.com
A heterogeneous short-range communication platform for
Internet of Vehicles
Naser Zaeri
Faculty of Computer Studies, Arab Open University, Kuwait
Article Info ABSTRACT
Article history:
Received Apr 29, 2020
Revised Sep 13, 2020
Accepted Oct 11, 2020
The automotive industry is rapidly accelerating toward the development of
innovative industry applications that feature management capabilities for
data and applications alike in cars. In this regard, more internet of vehicles
solutions are emerging through advancements of various wireless medium
access-control technologies and the internet of things. In the present work,
we develop a short-range communication–based vehicular system to support
vehicle communication and remote car control. We present a combined
hardware and software testbed that is capable of controlling a vehicle’s start-
up, operation and several related functionalities covering various vehicle
metric data. The testbed is built from two microcontrollers, Arduino and
Raspberry Pi 3, each of which individually controls certain functions to
improve the overall vehicle control. The implementation of the
heterogeneous communication module is based on the IEEE 802.11 and
IEEE 802.15 medium access control technologies. Further, a control module
on a smartphone was designed and implemented for efficient management.
Moreover, we study the system connectivity performance by measuring
various important parameters including the coverage distance, signal
strength, download speed and latency. This study covers the use of this
technology setup in different geographical areas over various time spans.
Keywords:
Bluetooth
Internet of vehicles
Sensors
Short-range communication
Wi-Fi connectivity performance
This is an open access article under the CC BY-SA license.
Corresponding Author:
Naser Zaeri
Faculty of Computer Studies
Arab Open University, P.O. Box 830 Ardiya, 92400, Kuwait
Email: n.zaeri@aou.edu.kw
1. INTRODUCTION
Recently, the internet of vehicles (IoV) has attracted researchers and engineers in the vehicle
industry and manufacturing. It is aimed to be an important component of the forthcoming intelligent
transportation system architecture that facilitates several functions expected to take place by the driver in
such a manner that it extends the driver’s ability to use on-board devices (e.g., radar or sensors) and, thus,
improve road traffic safety and efficiency [1]. Vehicle telemetry and metric data can include those
concerning or from the global positioning system (GPS), vehicle operations, engine performance and the
engine control system. The engine control system in particular can exhibit the ability to diagnose, record,
monitor, control and or optimise engine performance [2].
Actually, the IoV encompasses two main technology directions [3], vehicles’ networking and
vehicles’ intelligence. Vehicle networking is a term used to define a connected vehicle interchanging
electronic data and providing such information services as location-based information services, remote
diagnostics, on-demand navigation and audiovisual entertainment content. On the other hand, vehicles’
intelligence seeks to integrate the driver’s technological skills and the vehicle’s capabilities together as a

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Int J Elec & Comp Eng, Vol. 11, No. 3, June 2021 : 2165 - 2177
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single unit. This is accomplished by proposing advanced concepts such as deep learning, and cognitive
computing. In other words, IoV is an open and integrated network system with high manageability,
controllability and operationalisation that can involve multiple users, multiple vehicles, multiple components
and multiple networks [4].
In this work, we present a combined hardware and software testbed that is capable of controlling a
vehicle’s start-up, windows control and door security lock capacities and several related functionalities
covering various vehicle metric data. The testbed is built from two microcontrollers, Arduino [5] and
Raspberry Pi 3 [6], each of which controls certain functions to enhance the overall performance of the
vehicle' system. Meanwhile, both the controllers and the associated functions are controlled and driven by a
wireless communication system using two different technologies: Wi-Fi [7] and Bluetooth [8]. Further, the
proposed testbed is equipped with a computer-controlled centre console, allowing it to warn of hazards in
road traffic and enable the driver to better manage several inter-vehicle functions ranging from music to
navigation and climate systems using a smartphone. Moreover, we herein present a detailed study of the Wi-
Fi transmission and connectivity performance of the proposed system. This investigation covers the system’s
deployment in different geographical areas over various time spans, where we measure various important
factors and parameters that are vital to accurately assessing the performance of such a wireless
communication system. These parameters include the coverage distance, signal strength, download speed,
and latency.
The rest of this paper is organised as follows. Related work is briefly discussed in section 2. Section
3 covers the wireless medium access control technologies. Section 4 discusses the evolution of Wi-Fi and its
effects on the IoV. The proposed system architecture is provided in section 5. The experimental results are
presented and discussed in section 6. Finally, the paper is brought to a conclusion in section 7.
2. RELATED WORK
Shaokun et al. [9] studied the ARM9-structured processor and embedded Linux system as means to
drive improvements in the versatility and real-time capacity of a wireless remote-control car. The system
collected data using sensors and transmitted them to a PC console and the authors demonstrated that the
system can accomplish multiple tasks under safeguards in a timely fashion. Liu et al. [10] proposed adopting
vehicle communication methods to improve safety by way of wireless data exchange. The communication
structure is based on a message being sent that can be derived using non–vehicle-based technologies such as
GPS to identify the location and speed of a vehicle or by employing vehicle-based sensor data wherein the
location and speed data are derived from the vehicle’s computer and combined with other data such as
latitude, longitude or angle to produce a richer, more detailed situational awareness of the positioning of
other vehicles. To enhance the performance of vehicle communication, a new variation of wireless access in
the vehicular environment has been developed [11] that is capable of supporting a range of applications and
services belonging to intelligent transportation systems. Zheng et al. [12] used long-range Wi-Fi that can
provide improved radio coverage of up to more than 1 km as compared with other related options. Fangchun
et al. [3] discussed the mobility constraints related to vehicular networks, where the number of connected
vehicles is a major issue in this regard. Several characteristics of large cities, such as traffic jams, tall
buildings, poor behaviour by drivers and complex road networks, further complicate this matter. Also, Yuan
et al. [13] evaluated the performance of the IEEE 802.11 medium access control (MAC) protocol applied to
vehicle safety communications in a typical highway environment.
Lwin et al. [14] discussed signal propagation from an IEEE 802.11n access point being nonuniform
in the circumferential and height directions due to the multiple input-multiple output (MIMO) system of
antennas. As per their discussion, the data transmission speed between the access point and a host could be
significantly affected as a result of this and, to solve this problem, these authors proposed a minimax
approach for optimizing the setup condition in terms of the angles and the height in an indoor environment
using throughput measurements. Elsewhere, Raza et al. [15] proposed a new open-hardware platform for
Bluetooth low energy to be incorporated into internet of things (IoT) systems, while Xu et al. [16] described
an improved Wi-Fi method to replace GPS behaviour for the indoor environment, using a raw-data
smoothing technique with an ensemble classification neural network method to deal with noisy Wi-Fi signal
strength.
3. WIRELESS MEDIUM ACCESS CONTROL TECHNOLOGIES
Currently, there are different approaches to developing wireless MAC (the layer that controls the
hardware responsible for interaction with the media) for inter-vehicle communication that differ in terms of
the adopted radio interface. In this section, we briefly outline the main MAC technologies and their potential.

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A heterogeneous short-range communication platform for internet of vehicles (Naser Zaeri)
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3.1. Bluetooth
Bluetooth is a short-range wireless technology based on the IEEE 802.15.1 standard operating in the
industrial, scientific and medical (ISM) frequency band (2.4 GHz). It allows for the communication between
portable devices at a data rate of up to 3 Mbps and is highly commercialised for consumer electronics using a
spread spectrum, frequency-hopping full-duplex signal at a nominal rate of 1,600 hops/s [17]. Bluetooth uses
less power and costs less to implement relative to Wi-Fi. Its lower power makes it far less prone to suffering
from or causing interference with other wireless devices operating in the same 2.4-GHz radio band. These
advantages come at the expense of range and transmission speeds, however, which are typically lower than
those of Wi-Fi. Moreover, due to its poor scalability, a Bluetooth network can only support eight active
devices at maximum. Bluetooth devices are common in current automobiles, such as Bluetooth headsets and
rearview mirrors [8].
3.2. ZigBee
One option for enabling IoV connectivity is through the use of ZigBee technology, which is based
on the IEEE 802.15.4 standard and which operates on the ISM radio spectrum [18]. ZigBee is low-cost and
can provide an acceptable data rate (250 Kbps in the 2.4 GHz frequency band).
3.3. Radio-frequency identification (RFID)
The feasibility of using RFID technology for building intra-vehicle sensor networks has been
studied by the ZigBee alliance [19]. In this technology, each sensor is equipped with an RFID tag and a
reader connected to the vehicle’s electrical control unit periodically retrieves the sensed data by sending an
energizing pulse to each tag [20].
3.4. Ultra-wideband
Ultra-wideband (UWB) refers to radio technology that operates in the 3.1 to 10.6 GHz frequency
band and that can support short-range communications at a data rate of up to 480 Mbps and at a low energy
level [21]. UWB systems offer a number of advantages, such as resistance to severe wireless channel fading
as well as a high time-domain resolution suitable for localisation and tracking applications [22]. However,
proposing appropriate channel models able to capture the propagation characteristics of in-vehicle
environments, is a major challenge as the channel statistics are quite different from location to location.
Defining the most suitable transmission techniques at the physical (PHY) layer is a critical issue for UWB-
based intra-vehicle sensor networks [23].
3.5. Cellular technology using 3G/4G/LTE
The cellular technology extensions have the potential to support high granularity for data
transmission and flexible assigning of radio resources due to the CDMA/OFDMA component, yet suffer
from the complexity of designing a coordination function in an ad-hoc mode [24]. It should be noted that this
direction of research is accelerating rapidly in parallel with the Wi-Fi direction, especially with the emerging
adoption of 5G networks.
3.6. Wi-Fi
Wi-Fi technology, based on the IEEE wireless communication standard 802.11, has continually
improved, with each generation bringing about faster speeds, lower latency and enhanced user experiences in
a multitude of environments and with a variety of device types [25]. Basically, Wi-Fi enables networking
between computers and digital devices without the need for physical wires; instead, using high frequencies,
radio technologies can send data seemingly through the air over short distances. Devices adhering to the
802.11 standard run on either 2.4 GHz or 5 GHz, depending on their type. Several target groups have been
working toward different variations of the 802.11 family (e.g., 802.11 a/b/g/n/ac/ad/ax), all of which present
different characteristics and challenges that make them suitable for deployment in different environments
[26]. Overall, the 802.11 standard supports short radio coverage with relatively higher data rates. The
subsequent section will focus on Wi-Fi technology in more detail given that it has been adopted as the main
wireless communication medium in our system.
3.7. WiMAX
This wireless technology is affiliated with IEEE 802.16 a/e/m standards [27]. IEEE 802.16 standard-
based WiMAX systems are able to cover a large geographical area, up to 50 km and can deliver significant
bandwidth to end-users-in theory, up to 72 Mbps. While the IEEE 802.16 standard only supports fixed
broadband wireless communications, the IEEE 802.16e/mobile WiMAX standard supports speeds of up to
160 km/h and different classes of quality of service, even for non–line-of-sight transmissions. The key

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advantage of WiMAX relative to a wireless local area network (WLAN) is that the channel access method in
the former employs a scheduling algorithm that the subscriber station needs to follow only once for initial
entry into the network.
4. IoV AND THE EVOLUTION OF WI-FI
In 1999, Wi-Fi technology emerged as a promising technology to support the WLAN initiative,
which can enable the implementation of various kinds of applications that touch various aspects of our lives.
Several visionary companies came together to form a global nonprofit association with the goal of driving the
development and adoption of new wireless networking technology. In 2000, the group adopted the term
‘Wi-Fi’ as the proper name for its technical work and announced its official name: the Wi-Fi alliance [7]. The
term ‘Wi-Fi’ is used to describe a certified wireless networking product conforming to an industry standard
designated by the IEEE. Since 1999, various versions of Wi-Fi technologies have been proposed and
developed, with the early versions including IEEE802.11a, 802.11b and 802.11g. However, by 2009 and the
first launch of the 802.11n protocol, alongside consequent advancements in the technology, applications of
the IoV began to emerge as feasible. As such, we offer a brief description of IEEE 802.11n and its successor
versions below.
4.1. IEEE 802.11n
The IEEE 802.11n standard operates in the 2.4-GHz and 5-GHz bands and provides good coverage
across the home and office for everyday functions that do not require extensive amounts of bandwidth such
as browsing the Internet and managing smart home products [26, 28]. At this point, 802.11n devices have
become key enablers of smart living applications. Many of the IoT devices available now, from wearables to
televisions, have adopted this standard. Also, it offers a longer reach relative to those of preceding wireless
technologies and can support many client devices without sacrificing signal strength. Also, the power-saving
feature ensures longer sleep periods and reduces the need for devices to communicate with infrastructure too
frequently.
4.2. IEEE 802.11ad
The 802.11ad specification for the wireless transmission of data (originally for video-streams) in the
60-GHz band provides speeds in the multigigabit range [29]. In the range around 60 GHz, an unlicensed
frequency band between 57 and 64 GHz is available that permits higher channel bandwidths for greater
throughput and can provide global availability and avoid the overcrowded 2.4-GHz and 5-GHz bands. In fact,
it can support data rates of up to 8 Gbit/s and operate at different modes-for example, during energy-saving
mode for battery-operated devices and high-performance mode for very high throughput.
One of its anticipated applications is its use in small-cell backhaul [30]. Backhaul is the transmission
link between the small cell and the mobile network controller. Small-cell controllers can be deployed in the
streets (e.g., lampposts, streetlights), where their deployment cost is small as compared with that of optical
fibre. Another advantage is their small wavelengths (approximately 5 mm). These make it possible to use
compact and competitive antennas or antenna arrays for beamforming, which can be used to both focus
power to the receiver and help in optimizing power at the receiver. Further, beamforming can provide the
necessary antenna gain to compensate for the high free-space pass loss. This efficiently helps in overcoming
interference during transmission in real-time.
However, this range also has its disadvantages. For example, the field attenuation in this band is
very high, topping 68 dB after 1 m and even 90 dB after 10 m of travelling [31]. Nonetheless, the high degree
of attenuation can also be seen as an advantage because the transmission typically takes place within a
limited range (within 4 m), which means that interference from adjacent transmissions is more unlikely; as
such, the transmission becomes more secure.
4.3. IEEE 802.11ac
Through the use of MIMO antenna technology, this standard can reduce error and boost the speed.
The IEEE 802.11ac standard supports data rates of up to 3.46 Gbps and supports 40 MHz, 80 MHz and
160 MHz channel bandwidths as compared with just the 20 MHz and 40 MHz bandwidths supported by
802.11n. Further, 802.11ac supports up to eight spatial streams in contrast with the maximum of four
supported with 802.11n. The PHY data subcarriers are modulated using binary phase-shift keying, quadrature
phase-shift keying, 16-quadrature amplitude modulation (QAM), 64-QAM and 256-QAM [32].

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4.4. IEEE 802.11ax
This standard delivers improvements and new features that enable Wi-Fi devices to operate
efficiently in the densest and most dynamic connectivity settings. IEEE 802.11ax allows enterprises and
service providers to support new and emerging applications on the same WLAN infrastructure while
delivering a higher grade of service to older applications [33]. This scenario sets the stage for new business
models and increased Wi-Fi adoption and also powers more predictable performance for advanced
applications such as 4K video, ultra–high-definition, and IoT. Flexible wake-up time scheduling lets client
devices sleep much longer than with 802.11ac and wake up to less contention, extending the battery life of
smartphones, IoT and other devices. The PHY data subcarriers in IEEE 802.11ax are modulated using 1024-
QAM. IEEE 802.11ax achieves its benefits by highlighting the following dimensions:
− Orthogonal frequency division multiple access (OFDMA), which effectively shares channels to increase
the network efficiency and lower latency for both uplink and downlink traffic in high-demand
environments [34]
− Multi-user MIMO, which allows more downlink data to be transferred at one time, enabling access points
to concurrently handle more devices
− 160-MHz channel use capability, which increases the bandwidth needed to deliver greater performance
with low latency
− Transmit beamforming, which enables higher data rates at a given range to increase network capacity
− Robust high-efficiency signalling for better operation at a significantly lower received-signal-strength-
indication (RSSI)
Of these, OFDMA is especially beneficial for conducting multiple short transmissions in wide
channels since many data transmissions follow the same PHY header and channel access timeout. Moreover,
OFDMA allows better coping with fading and, improves the spectral power density. The efficiency of
OFDMA depends upon how the access point schedules channel resources among the different stations and on
how it configures other transmission parameters, such as the transmission power. Table 1 summarises some
important characteristics of Wi-Fi versions including the earlier versions-namely, 802.11a/b/g. CCK, which
stands for complementary code keying, was a short-lived deviation that existed prior to the huge
advancements reached by OFDM in later versions.
Table 1. Wi-Fi versions
Standard Year Band/GHz Modulation method Highest modulation order Highest code rate
802.11a 1999 5 OFDM 64-QAM 3/4
802.11b 1999 2.4 CCK QPSK 1/2
802.11g 2003 2.4 OFDM 64-QAM 3/4
802.11n 2009 2.4/5 OFDM 64-QAM 5/6
802.11ad 2012 60 OFDM 64-QAM 13/16
802.11ac 2014 5 OFDM 256-QAM 5/6
802.11ax 2019 2.4/5 OFDM 1024-QAM 5/6
5. SYSTEM ARCHITECTURE
Different from generic wireless sensor networks, intra-vehicle wireless sensor networks show
unique characteristics that provide the space for optimisation. For example, the sensors in intra-vehicle
networks are stationary so that the network topology does not change over time. Also, these sensors are
typically connected through one hop, which yields a simple star-topology. Further, with this arrangement,
there is no energy constraint for sensors having wired connections to the vehicle power system.
A typical IoV architecture consists of the following three layers:
− The perception layer, which contains all sensors within the vehicle that gather data and detect specific
events of interest; it also boasts RFID, satellite-positioning perception, road-environment perception,
vehicle-position perception and other-object-placement perception capabilities.
− The network layer, which is the communication layer that ensures connectivity to communications
networks such as 3G/4G/5G, WiMax, WLAN, Wi-Fi and Bluetooth.
− The application layer, which is responsible for storage, analysis, processing and decision-making
concerning different risk situations such as traffic congestion and bad weather; it also encompasses smart
applications, traffic safety, efficiency and multimedia-based infotainment components.
We herein propose a system that is composed of two microprocessors (Arduino and Raspberry Pi 3)
monitored by an Android-based platform. In this arrangement, both microprocessors and the associated
functions are governed by wireless communication systems using Wi-Fi and Bluetooth technologies. In
addition, the system is connected to a touchscreen monitor and a microphone to minimise driving distraction

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and ease car control via the use of voice. Figure 1 shows the proposed vehicle communication system
architecture. As demonstrated in Figure 1, each one of the two microcontrollers controls certain
functionalities. The Raspberry Pi 3 microprocessor, shown in Figure 2, uses Samsung’s (Seoul, South Korea)
S5 CPU 1.2-GHz 64-bit plus 1 GB of RAM and enables Bluetooth and Wi-Fi connections. This processor
requires a power adapter to feed it with a steady 2.5-A current for proper performance. Meanwhile, the
Raspberry Pi control system consists of the SDK library, which provides support for all Android auto
features. Also, it provides support for the asynchronous mechanisms inherent in communication, multimedia,
user input and graphical interface actions. The system uses OpenSSL for encrypting communication. The
Raspberry Pi microcontroller controls and supports components of the vehicle’s built-in infotainment system
such as audio, phone calls and navigation.
Figure 1. The proposed vehicle system communication architecture
Figure 2. Raspberry Pi 3 microprocessor
The other microprocessor is the Arduino one. Arduino, shown in Figure 3, is an open-source
computer hardware and software platform that supports the design and creation of mini-controllers [5].
Further, it enables Bluetooth and Wi-Fi connections. The Arduino microprocessor is connected to a relay as
shown in Figure 4 that controls the electrical circuit board. This board is connected to a 12-V battery. The
ignition wire and vehicle windows’ electricity wires are connected to this board as well.
The relay used in this design was a four-channel relay module. In this arrangement, the switching
mechanism is deployed out with the help of an electromagnet. The relay cards are connected to act as an H-
bridge drive. One end of the relay card is connected to the microcontroller and the other end is connected to
the terminals of the motor of the window in the car arm. The forward, stop and reverse motions of the
window are controlled using the relay card, i.e., the supply voltage to the motor can be changed in either of
the directions, causing clockwise and anti-clockwise motions of the motor. Further, the system is connected
to an 800×480 display as shown in Figure 5 via an adapter board, which handles power and signal

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conversion. The touchscreen display supports an on-screen keyboard for full functionality without a physical
keyboard or mouse. Finally, a microphone is connected to the system to enable handling voice commands.
Figure 3. Arduino microprocessor
Figure 4. The electrical relay used in the Arduino board connection
Figure 5. 800×480 display used in system control
6. EXPERIMENTAL RESULTS AND DISCUSSION
We began this investigation by installing the corresponding operating system on the two
microprocessors. Regarding the Raspberry Pi 3, the Raspbian operating system comes preinstalled with
Python, Scratch, Sonic Pi and Java. As for the Arduino microprocessor, it is configured using the C
programming language. Several functionalities were coded and implemented. First, the system was
configured to handle all notifications, calls and emergency calls. If a call is received, the system will
automatically reply with a preset message. Also, it can handle many popular applications such as Google
Hangouts, Facebook messenger and WhatsApp. Second, the system can be synchronised with the mobile
phone to migrate the user’s contacts, calendars, music library and saved locations. Third, a navigation system
has been launched on the system, where the driver can use Google Maps in an easy manner through voice
control. The voice control enables the driver to enter new destinations, set favourite addresses, stop route

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guidance and set up auto-navigation. In addition, checking and reading emails and SMS text messages is
accomplished in a similar manner. The abovementioned functionalities are controlled remotely through an
interface using a touchpad/mobile phone via the Bluetooth 802.15 technology. Furthermore, the system is
configured to control the following functions remotely using the Wi-Fi 802.11 technology:
− Starting and turning off the engine remotely without a key
− Unlocking /locking the doors
− Pulling windows up and down
Moreover, the system enables the user to set a password of his/her choice to keep the system
protected. A theft alarm is integrated into the system that alerts when an unusual activity is sensed or when a
wrong password is attempted to unlock the system. To achieve this, the car ignition wire is connected to the
on-board diagnostics (OBD) port of the car. If a correct password is entered, then the system will verify it
and an acknowledgement (ACK) is sent. Hence, a wireless connection is established between the two control
units and the remote console can perform the functions accordingly. The system interface for the Arduino
functions is shown in Figure 6.
Figure 6. System interface for the Arduino functions
To test the visibility of the system and assess its performance, we conducted extensive experimental
studies, focusing on the three most important parameters in any wireless communication system-that is, we
studied the signal strength, download speed and latency. The performance of a wireless communication
system, including the system at hand, is technically evaluated by assessing how efficient these parameters
can perform in real-life practical scenarios. With respect to radio-frequency, signal strength refers to the
transmitter power output as received by a reference antenna at a distance from the transmitting antenna. For
very-low-power systems, such as mobile phones, signal strength is usually expressed in dBm, which stands
for decibels relative to a milliwatt. The signal strength required for optimal performance varies according to
many factors such as background noise in the environment, the amount of clients on the network, what the
desired data rates are and what applications will be used.
Moreover, network speed is measured by how much data the connection can download (download
speed) or upload (upload speed) per second. It indicates the total maximum data-carrying capacity of the
network in optimum conditions. Generally, a little over half of this capacity is consumed by management and
control traffic. The remaining capacity is available for user data. This capacity is referred to as throughput
and is usually expressed in bits per second (bit/s). For most applications, having fast download speeds reflect
to a far extent the successful implementation of the network. This is much more readily apparent in common
activities such as watching streaming television, downloading music and browsing the Internet. The
throughput of a wireless LAN is linked to many other factors including the data-carrying capacity, local
interference, environment (obstructions), equipment setup (including antenna orientation) and the
transmission power. Furthermore, the latency refers to the amount of delay (or time) it takes to send
information from one point to the next. Latency is usually measured in milliseconds (ms) and is also referred
to (during speed tests) as a ping rate. One of the major reasons for poor latency is nonoptimal geography,
although other important reasons that may affect the latency include the transmission media and packet size.

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In measuring the abovementioned parameters, we used various mobile applications as shown in
Table 2. Further, we have considered various scenarios as part of this research. Specifically, we conducted
the measurements in eight different geographical locations, including some urban and suburban ones.
Moreover, we operated the system on various traffic applications, including voice over internet protocol
(VoIP), video-watching, web surfing and sending emails. The duration time required for each session
readings setup was between one and three hours and 20 to 60 different readings were taken in each session.
The readings were repeated three times for each location over a one-month span time and the average of the
readings was considered to represent the final readings.
Table 2. Experimental scenario parameters
Parameters Description
Applications used Wi-Fi Speed Test, Open Signal, Wi-Fi Signal Meter,
Network Signal Information
Wireless technologies Wi-Fi
Standard IEEE 802.11
Frequency bands 2.4 GHz, 5 GHz
Traffic application VoIP, video, HTTP, email
Scenario Urban, suburban
Number of locations (test areas) 8
Number of readings per location 20–60
Experimental time per test 1–3 hours
Figure 7 shows an example of a signal strength test for a specific area. Figure 8 shows the average
readings of the signal strength in dBm for all eight locations. Further, an example of a download speed test is
shown in Figure 9. The average download speeds for all eight locations are given in Figure 10. Finally, the
corresponding average latency is given in Figure 11.
Figure 7. An example of a signal strength test for a specific area
Figure 8. Average signal strength versus distance for the eight locations

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Figure 9. An example of a download speed test
Figure 10. Average downloads speed versus distance for the eight locations
Figure 11. Average latency versus distance for the eight locations
Notably, the following remarks should be considered when viewing Figures 7 and 8. The signal
strength varies from one location to another but, in general, the system is capable of receiving signals up to
almost 100 m. Controlling the vehicle’s different applications depends upon the data nature of each one of
these applications. More specifically, we were able to successfully operate all the system functionalities up to
30 m, where the strength reaches around -65 dBm. This includes navigation, VoIP and streaming video. The
connection was reliable and the timely delivery of data packets was observed. Further, the signal strength
decreases to almost -80 dBm at a distance of 60 m. Though this level of signal is low, some necessary
applications were still able to function reliably, such as email, web browsing and the ability to call the police
and emergency services. Of course, the signal strength decreased further as the distance increased from here,

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ultimately reaching levels of less than -90 dBm at distances of 80 meters. At this level, only two applications
could successfully be controlled: the door lock system and car ignition; these control functions were
maintained up to almost 100 m.
However, some exceptions were noticed as well. For example, system performance at some
locations was below the average and full successful functionalities were barely attained at a distance of 30 m.
This may be explained by the fact that specific sites can be characterised by significant traffic congestion
throughout the day. In this context, the signal reflection is high and severely affects the transmission.
The above discussion regarding signal strength and system functionality performance is reinforced
when we further examine Figures 9 and 10, which present the download speeds. We were able to attain an
average of 6 Mbps at distances as far as 80 m. Actually, in two of the eight locations under study, the
download speed was around 10 Mbps.
On the other hand, a noticeable variation in time latency was recognised among the various locations.
For example, at a distance of 20 m, the readings of latency varied from less than 20 ms to almost 200 ms. A
remarkable issue that was observed in this regard is the delay variation between the 2.4-GHz and 5-GHz
bands. We noticed that the connection under the 5-GHz band was more consistent than that with the 2.4 GHz
one. Nonetheless, this variation did not affect the successful operation of the various applications. In brief,
these results demonstrate the successful design and implementation of the proposed system, where the
combined hardware and software testbed verified an effective capability for controlling a vehicle’s different
functionalities.
7. CONCLUSION AND FUTURE WORK
In this paper, we presented a heterogeneous short-range communication platform for IoV based on
IEEE 802.11 and 802.15 technologies. A combined hardware and software testbed was built to control
several important vehicle functionalities including start-up, movement of windows, door security locking,
hazard warnings in road traffic, navigation, climate systems and several other inter-vehicle functions. The
testbed was built from two microcontrollers: Arduino and Raspberry Pi 3. Further, a control module on a
smartphone was designed and implemented for efficient remote management. Moreover, we implemented
extensive experimental studies on the Wi-Fi transmission and connectivity performance of the proposed
system to evaluate its efficiency in real-life practical scenarios. Our research considered several important
parameters-mainly, the signal strength, download speed, and latency. All system functionalities including
navigation, VoIP and video streaming successfully operated up to a 30-m distance, where the average signal
strength was greater than -65 dBm and the average download speed was around 20 Mbps. Despite the
decrease in signal strength at larger distances, the system maintained successful control of the main vehicle’s
functions-that is, the door lock security system and car ignition-up to 100 m away.
However, there remain many challenges that face IoV and slow down its full and widespread
adoption. For example, IoV involves the integration of different services and standards that may attract
intruders and cyber-attacks. Hence, security plays an important role in this aspect. The reliability of sensors
and network coverage are other important challenges that need to be tackled by researchers to ensure proper
functioning and effective signal communications in real time. These issues will be addressed in our future
work, where we aim to integrate the current system with 4G LTE/5G systems.
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BIOGRAPHY OF AUTHOR
Naser Zaeri is an associate professor with the Department of Information Technology and
Computing (ITC) at the Arab Open University (AOU), Kuwait. He has obtained his PhD in
Electrical Engineering from University of Surrey, United Kingdom in 2008. He has obtained his
M.Sc. and B.Sc. degrees in Electrical Engineering from Kuwait University (Honor List). He
served as the Director of Research and Development at the AOU during (2012 – 2014). He was
the Head of ITC Department at the AOU during (2010 – 2012). Also, he was with College of
Engineering and Petroleum - Kuwait University, as a lecturer. He served as a consultant for
many authorities and ministries. Dr. Zaeri has participated in and in charge of many projects in
different fields of engineering and technology. He has more than 40 different publications in
international journals and conferences. His areas of interest are: communications systems, digital
image processing, biometrics, and pattern classification.

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